Use an Engine
# knitr::opts_chunk$set(echo = TRUE)
require(SASmarkdown)## Loading required package: SASmarkdown## sas, saslog, sashtml, and sashtmllog engines## are now ready to use.saspath <- "C:/Program Files/SASHome/SASFoundation/9.4/sas.exe"
sasopts <- "-nosplash -ls 75"
knitr::opts_chunk$set(engine='sashtml', engine.path=saspath,
engine.opts=sasopts, comment="")Generally, can not use r syntax in these chunks
Data can not be used in different chunks
proc means data=sashelp.class ;
run;
proc freq data=sashelp.class ;
table sex;
run;
proc contents data=sashelp.class varnum ;
run;
The MEANS Procedure
Variable N Mean Std Dev Minimum Maximum
-------------------------------------------------------------------------
Age 19 13.3157895 1.4926722 11.0000000 16.0000000
Height 19 62.3368421 5.1270752 51.3000000 72.0000000
Weight 19 100.0263158 22.7739335 50.5000000 150.0000000
-------------------------------------------------------------------------
The FREQ Procedure
Cumulative Cumulative
Sex Frequency Percent Frequency Percent
--------------------------------------------------------
F 9 47.37 9 47.37
M 10 52.63 19 100.00
The CONTENTS Procedure
Data Set Name SASHELP.CLASS Observations 19
Member Type DATA Variables 5
Engine V9 Indexes 0
Created 09/06/2017 22:55:32 Observation Length 40
Last Modified 09/06/2017 22:55:32 Deleted Observations 0
Protection Compressed NO
Data Set Type Sorted NO
Label Student Data
Data Representation WINDOWS_64
Encoding us-ascii ASCII (ANSI)
Engine/Host Dependent Information
Data Set Page Size 65536
Number of Data Set Pages 1
First Data Page 1
Max Obs per Page 1632
Obs in First Data Page 19
Number of Data Set Repairs 0
ExtendObsCounter YES
Filename C:\Program
Files\SASHome\SASFoundation\9.
4\core\sashelp\class.sas7bdat
Release Created 9.0401M5
Host Created X64_SR12R2
Owner Name BUILTIN\Administrators
File Size 128KB
File Size (bytes) 131072
Variables in Creation Order
# Variable Type Len
1 Name Char 8
2 Sex Char 1
3 Age Num 8
4 Height Num 8
5 Weight Num 8proc sort data=sashelp.class Out= name ;
by name;
Run;
proc print data= name (obs=10) ;
run; Obs Name Sex Age Height Weight
1 Alfred M 14 69.0 112.5
2 Alice F 13 56.5 84.0
3 Barbara F 13 65.3 98.0
4 Carol F 14 62.8 102.5
5 Henry M 14 63.5 102.5
6 James M 12 57.3 83.0
7 Jane F 12 59.8 84.5
8 Janet F 15 62.5 112.5
9 Jeffrey M 13 62.5 84.0
10 John M 12 59.0 99.5proc transpose data= sashelp.class out= Field;
by name;
Run;
proc print data= field (obs=10) ;
run; Obs Name _NAME_ COL1
1 Alfred Age 14.0
2 Alfred Height 69.0
3 Alfred Weight 112.5
4 Alice Age 13.0
5 Alice Height 56.5
6 Alice Weight 84.0
7 Barbara Age 13.0
8 Barbara Height 65.3
9 Barbara Weight 98.0
10 Carol Age 14.0
DATA ab;
set sashelp.class;
IF sex="F" then message='A is greater';
Else message='B is greater';
Run;
proc print data=ab (obs=10);
run; Obs Name Sex Age Height Weight message
1 Alfred M 14 69.0 112.5 B is greater
2 Alice F 13 56.5 84.0 A is greater
3 Barbara F 13 65.3 98.0 A is greater
4 Carol F 14 62.8 102.5 A is greater
5 Henry M 14 63.5 102.5 B is greater
6 James M 12 57.3 83.0 B is greater
7 Jane F 12 59.8 84.5 A is greater
8 Janet F 15 62.5 112.5 A is greater
9 Jeffrey M 13 62.5 84.0 B is greater
10 John M 12 59.0 99.5 B is greaterproc format;
value AGEnew
11 = '1: NEW'
12 = '2: NEW'
13 = '3: NEW'
14 = '4: NEW'
15 = '5: NEW'
16 = '6: NEW'
;
run;
DATA ab;
set sashelp.class;
Format AGE AGEnew.;
Run;
proc freq data=ab;
table AGE;
run;
The FREQ Procedure
Cumulative Cumulative
Age Frequency Percent Frequency Percent
-----------------------------------------------------------
1: NEW 2 10.53 2 10.53
2: NEW 5 26.32 7 36.84
3: NEW 3 15.79 10 52.63
4: NEW 4 21.05 14 73.68
5: NEW 4 21.05 18 94.74
6: NEW 1 5.26 19 100.00 Data Mathdata;
A= 10.12345;
B=20;
C= mean (a,b);
D= Min(a,b);
E= Max(a,b);
F = log(a);
G= round(a,0.02);
H= floor(a );
Run;
proc print data=Mathdata;
run;
Data mathdata;
Set sashelp.Iris;
Sum = sum (of SepalLength, SepalWIDTH);
Diff = SepalLength- SepalWIDTH;
Mult = SepalLength* SepalWIDTH;
Div= SepalLength/ SepalWIDTH;
Run;
proc print data=mathdata (obs=10);
run;Obs A B C D E F G H
1 10.1235 20 15.0617 10.1235 20 2.31485 10.12 10
Sepal Sepal Petal Petal
Obs Species Length Width Length Width Sum Diff Mult Div
1 Setosa 50 33 14 2 83 17 1650 1.51515
2 Setosa 46 34 14 3 80 12 1564 1.35294
3 Setosa 46 36 10 2 82 10 1656 1.27778
4 Setosa 51 33 17 5 84 18 1683 1.54545
5 Setosa 55 35 13 2 90 20 1925 1.57143
6 Setosa 48 31 16 2 79 17 1488 1.54839
7 Setosa 52 34 14 2 86 18 1768 1.52941
8 Setosa 49 36 14 1 85 13 1764 1.36111
9 Setosa 44 32 13 2 76 12 1408 1.37500
10 Setosa 50 35 16 6 85 15 1750 1.42857 Data AB;
set sashelp.class; Rename AGE= AGENEW;
Run;
proc print data=AB;
run; Obs Name Sex AGENEW Height Weight
1 Alfred M 14 69.0 112.5
2 Alice F 13 56.5 84.0
3 Barbara F 13 65.3 98.0
4 Carol F 14 62.8 102.5
5 Henry M 14 63.5 102.5
6 James M 12 57.3 83.0
7 Jane F 12 59.8 84.5
8 Janet F 15 62.5 112.5
9 Jeffrey M 13 62.5 84.0
10 John M 12 59.0 99.5
11 Joyce F 11 51.3 50.5
12 Judy F 14 64.3 90.0
13 Louise F 12 56.3 77.0
14 Mary F 15 66.5 112.0
15 Philip M 16 72.0 150.0
16 Robert M 12 64.8 128.0
17 Ronald M 15 67.0 133.0
18 Thomas M 11 57.5 85.0
19 William M 15 66.5 112.0Data Mathdata;
Text = "Hello World";
Text1= substr(Text, 6, 2);
Run;
proc print data=mathdata ;
run; Obs Text Text1
1 Hello World W Data ABC;
set sashelp.class;
agenew= input (age, best.);
Run;
proc print data=abc ;
run;
Obs Name Sex Age Height Weight agenew
1 Alfred M 14 69.0 112.5 14
2 Alice F 13 56.5 84.0 13
3 Barbara F 13 65.3 98.0 13
4 Carol F 14 62.8 102.5 14
5 Henry M 14 63.5 102.5 14
6 James M 12 57.3 83.0 12
7 Jane F 12 59.8 84.5 12
8 Janet F 15 62.5 112.5 15
9 Jeffrey M 13 62.5 84.0 13
10 John M 12 59.0 99.5 12
11 Joyce F 11 51.3 50.5 11
12 Judy F 14 64.3 90.0 14
13 Louise F 12 56.3 77.0 12
14 Mary F 15 66.5 112.0 15
15 Philip M 16 72.0 150.0 16
16 Robert M 12 64.8 128.0 12
17 Ronald M 15 67.0 133.0 15
18 Thomas M 11 57.5 85.0 11
19 William M 15 66.5 112.0 15 Data ABC;
set sashelp.class;
agenew= put (age, best.);
Run;
proc contents data=abc ;
run; The CONTENTS Procedure
Data Set Name WORK.ABC Observations 19
Member Type DATA Variables 6
Engine V9 Indexes 0
Created 07/06/2022 11:57:24 Observation Length 48
Last Modified 07/06/2022 11:57:24 Deleted Observations 0
Protection Compressed NO
Data Set Type Sorted NO
Label
Data Representation WINDOWS_64
Encoding wlatin1 Western (Windows)
Engine/Host Dependent Information
Data Set Page Size 65536
Number of Data Set Pages 1
First Data Page 1
Max Obs per Page 1361
Obs in First Data Page 19
Number of Data Set Repairs 0
ExtendObsCounter YES
Filename C:\Users\hed2\AppData\Local\Temp\1\SAS
Temporary
Files\_TD17236_HDW02234493_\abc.sas7bdat
Release Created 9.0401M5
Host Created X64_10PRO
Owner Name NIH\hed2
File Size 128KB
File Size (bytes) 131072
Alphabetic List of Variables and Attributes
# Variable Type Len
3 Age Num 8
4 Height Num 8
1 Name Char 8
2 Sex Char 1
5 Weight Num 8
6 agenew Char 12Data ABC;
set sashelp.class;
Length agenew $10.;
Label agenew=“New age”;
Run;
proc contents data=abc ;
run;
The CONTENTS Procedure
Data Set Name WORK.ABC Observations 19
Member Type DATA Variables 6
Engine V9 Indexes 0
Created 07/06/2022 11:57:24 Observation Length 48
Last Modified 07/06/2022 11:57:24 Deleted Observations 0
Protection Compressed NO
Data Set Type Sorted NO
Label
Data Representation WINDOWS_64
Encoding wlatin1 Western (Windows)
Engine/Host Dependent Information
Data Set Page Size 65536
Number of Data Set Pages 1
First Data Page 1
Max Obs per Page 1361
Obs in First Data Page 19
Number of Data Set Repairs 0
ExtendObsCounter YES
Filename C:\Users\hed2\AppData\Local\Temp\1\SAS
Temporary
Files\_TD16664_HDW02234493_\abc.sas7bdat
Release Created 9.0401M5
Host Created X64_10PRO
Owner Name NIH\hed2
File Size 128KB
File Size (bytes) 131072
Alphabetic List of Variables and Attributes
# Variable Type Len Label
3 Age Num 8
4 Height Num 8
1 Name Char 8
2 Sex Char 1
5 Weight Num 8
6 agenew Char 10 “New age”proc report data=sashelp.class;
Column age;
Define age / display;
Run; Age
14
13
13
14
14
12
12
15
13
12
11
14
12
15
16
12
15
11
15data ab;
set sashelp.class;
num=rand("normal");
run;
proc print data=ab (obs=10);
run; Obs Name Sex Age Height Weight num
1 Alfred M 14 69.0 112.5 0.53129
2 Alice F 13 56.5 84.0 1.46501
3 Barbara F 13 65.3 98.0 1.79722
4 Carol F 14 62.8 102.5 -0.68748
5 Henry M 14 63.5 102.5 0.52371
6 James M 12 57.3 83.0 1.01352
7 Jane F 12 59.8 84.5 0.56256
8 Janet F 15 62.5 112.5 0.47257
9 Jeffrey M 13 62.5 84.0 0.88518
10 John M 12 59.0 99.5 0.67657Data Mathdata;
Text = "Hello";
Text1= "World";
Text2= text || " " ||text1;
Run;
proc print data=Mathdata ;
run; Obs Text Text1 Text2
1 Hello World Hello WorldData Mathdata;
Text = "Hello World ";
Text1= trim(text);
Text2= compress(text);
Run;
proc print data=Mathdata ;
run; Obs Text Text1 Text2
1 Hello World Hello World HelloWorldData Mathdata;
Text = "Hello World";
indextext= index(text, "or");
Run;
proc print data=Mathdata ;
run; Obs Text indextext
1 Hello World 8 Data Mathdata;
Text = "Hello World";
upcase= upcase(text );
lowcase= lowcase(text );
propcase= propcase(text );
Run;
proc print data=Mathdata ;
run; Obs Text upcase lowcase propcase
1 Hello World HELLO WORLD hello world Hello World/* Dedup, original data has 19 observations */
proc sort data = sashelp.class out = dedup
nodupkeys;
by height;
run;
proc print data= dedup;
run;
Obs Name Sex Age Height Weight
1 Joyce F 11 51.3 50.5
2 Louise F 12 56.3 77.0
3 Alice F 13 56.5 84.0
4 James M 12 57.3 83.0
5 Thomas M 11 57.5 85.0
6 John M 12 59.0 99.5
7 Jane F 12 59.8 84.5
8 Janet F 15 62.5 112.5
9 Carol F 14 62.8 102.5
10 Henry M 14 63.5 102.5
11 Judy F 14 64.3 90.0
12 Robert M 12 64.8 128.0
13 Barbara F 13 65.3 98.0
14 Mary F 15 66.5 112.0
15 Ronald M 15 67.0 133.0
16 Alfred M 14 69.0 112.5
17 Philip M 16 72.0 150.0data where;
set sashelp.class;
where sex ne "F";
/*if */
run;
proc print data= where;
run; Obs Name Sex Age Height Weight
1 Alfred M 14 69.0 112.5
2 Henry M 14 63.5 102.5
3 James M 12 57.3 83.0
4 Jeffrey M 13 62.5 84.0
5 John M 12 59.0 99.5
6 Philip M 16 72.0 150.0
7 Robert M 12 64.8 128.0
8 Ronald M 15 67.0 133.0
9 Thomas M 11 57.5 85.0
10 William M 15 66.5 112.02 /*create a macro to calcualte descriptive stats */
3 %macro means(var_avg) ;
4
5 /*calculate means*/
6 proc means data=sashelp.class StackODSOutput n mean std min p5
6 ! p95 max nmiss;
7 var &var_avg;
8 class sex;
9 ods output summary=result2;
10 run;
11
12 /*append then output*/
13 data masterresult2; * combine results;
14 set masterresult2 result2;
15 run;
16
17 %mend means;
18
19 /*use macro to merge all descriptive stats */
20 data masterresult2 ;
21 set _null_;
22 run;
NOTE: The data set WORK.MASTERRESULT2 has 0 observations and 0 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
23
24 %let vars=
25 age
26 height
27 weight
28 ;
29
30 %macro model ;
31 %do i=1 %to %sysfunc(countw(&vars));
32
33 %let x=%scan(&vars,&i);
34 %means( &x )
35
36 %end;
37 %mend model;
38
39 %model;
NOTE: The data set WORK.RESULT2 has 2 observations and 12 variables.
NOTE: There were 19 observations read from the data set SASHELP.CLASS.
NOTE: The PROCEDURE MEANS printed page 1.
NOTE: PROCEDURE MEANS used (Total process time):
real time 0.03 seconds
cpu time 0.04 seconds
NOTE: There were 0 observations read from the data set WORK.MASTERRESULT2.
NOTE: There were 2 observations read from the data set WORK.RESULT2.
NOTE: The data set WORK.MASTERRESULT2 has 2 observations and 12 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
NOTE: The data set WORK.RESULT2 has 2 observations and 12 variables.
NOTE: There were 19 observations read from the data set SASHELP.CLASS.
NOTE: The PROCEDURE MEANS printed page 2.
NOTE: PROCEDURE MEANS used (Total process time):
real time 0.00 seconds
cpu time 0.01 seconds
WARNING: Multiple lengths were specified for the variable Variable by
input data set(s). This can cause truncation of data.
NOTE: There were 2 observations read from the data set WORK.MASTERRESULT2.
NOTE: There were 2 observations read from the data set WORK.RESULT2.
NOTE: The data set WORK.MASTERRESULT2 has 4 observations and 12 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.01 seconds
NOTE: The data set WORK.RESULT2 has 2 observations and 12 variables.
NOTE: There were 19 observations read from the data set SASHELP.CLASS.
NOTE: The PROCEDURE MEANS printed page 3.
NOTE: PROCEDURE MEANS used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
WARNING: Multiple lengths were specified for the variable Variable by
input data set(s). This can cause truncation of data.
NOTE: There were 4 observations read from the data set WORK.MASTERRESULT2.
NOTE: There were 2 observations read from the data set WORK.RESULT2.
NOTE: The data set WORK.MASTERRESULT2 has 6 observations and 12 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
40
41 proc print data= masterresult2;
42 run;
NOTE: There were 6 observations read from the data set WORK.MASTERRESULT2.
NOTE: The PROCEDURE PRINT printed page 4.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
43 The MEANS Procedure
Analysis Variable : Age
N
Sex Obs N Mean Std Dev Minimum 5th Pctl
--------------------------------------------------------------------------
F 9 9 13.222222 1.394433 11.000000 11.000000
M 10 10 13.400000 1.646545 11.000000 11.000000
--------------------------------------------------------------------------
Analysis Variable : Age
N N
Sex Obs 95th Pctl Maximum Miss
------------------------------------------------
F 9 15.000000 15.000000 0
M 10 16.000000 16.000000 0
------------------------------------------------
The MEANS Procedure
Analysis Variable : Height
N
Sex Obs N Mean Std Dev Minimum 5th Pctl
--------------------------------------------------------------------------
F 9 9 60.588889 5.018328 51.300000 51.300000
M 10 10 63.910000 4.937937 57.300000 57.300000
--------------------------------------------------------------------------
Analysis Variable : Height
N N
Sex Obs 95th Pctl Maximum Miss
------------------------------------------------
F 9 66.500000 66.500000 0
M 10 72.000000 72.000000 0
------------------------------------------------
The MEANS Procedure
Analysis Variable : Weight
N
Sex Obs N Mean Std Dev Minimum 5th Pctl
--------------------------------------------------------------------------
F 9 9 90.111111 19.383914 50.500000 50.500000
M 10 10 108.950000 22.727186 83.000000 83.000000
--------------------------------------------------------------------------
Analysis Variable : Weight
N N
Sex Obs 95th Pctl Maximum Miss
------------------------------------------------
F 9 112.500000 112.500000 0
M 10 150.000000 150.000000 0
------------------------------------------------
Obs Sex NObs _control_ Variable N Mean StdDev
1 F 9 Age 9 13.222222 1.394433
2 M 10 1 Age 10 13.400000 1.646545
3 F 9 Hei 9 60.588889 5.018328
4 M 10 1 Hei 10 63.910000 4.937937
5 F 9 Wei 9 90.111111 19.383914
6 M 10 1 Wei 10 108.950000 22.727186
Obs Min P5 P95 Max NMiss
1 11.000000 11.000000 15.000000 15.000000 0
2 11.000000 11.000000 16.000000 16.000000 0
3 51.300000 51.300000 66.500000 66.500000 0
4 57.300000 57.300000 72.000000 72.000000 0
5 50.500000 50.500000 112.500000 112.500000 0
6 83.000000 83.000000 150.000000 150.000000 0 ods listing close;
ods trace on;
ods output ParameterEstimates= ParameterEstimates ;
proc glm data=sashelp.class;
model height=age;
run;
ods trace off;
ods listing;
proc print data=ParameterEstimates;
run;
Obs Dependent Parameter Estimate StdErr tValue Probt
1 Height Intercept 25.22388451 6.52168912 3.87 0.0012
2 Height Age 2.78713911 0.48688163 5.72 <.0001right, left join
2 data class2;
3 input name $ score;
4 datalines;
NOTE: The data set WORK.CLASS2 has 3 observations and 2 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
8 ;
9 run;
10
11 proc sql;
12 create table class_c as
13 select *
14 from sashelp.class as a
15 left join class2 as b
16 on a.name = b.name;
WARNING: Variable name already exists on file WORK.CLASS_C.
NOTE: Table WORK.CLASS_C created, with 19 rows and 6 columns.
17 quit;
NOTE: PROCEDURE SQL used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
18
19 proc print data=class_c;
20 run;
NOTE: There were 19 observations read from the data set WORK.CLASS_C.
NOTE: The PROCEDURE PRINT printed page 1.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
21
22 proc sql;
23 create table class_d as
24 select *
25 from class2 as a
26 right join sashelp.class as b
27 on a.name = b.name;
WARNING: Variable Name already exists on file WORK.CLASS_D.
NOTE: Table WORK.CLASS_D created, with 19 rows and 6 columns.
28 quit;
NOTE: PROCEDURE SQL used (Total process time):
real time 0.00 seconds
cpu time 0.01 seconds
29
30 proc print data=class_d;
31 run;
NOTE: There were 19 observations read from the data set WORK.CLASS_D.
NOTE: The PROCEDURE PRINT printed page 2.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
32 Obs Name Sex Age Height Weight score
1 Alfred M 14 69.0 112.5 85
2 Alice F 13 56.5 84.0 89
3 Barbara F 13 65.3 98.0 .
4 Carol F 14 62.8 102.5 .
5 Henry M 14 63.5 102.5 .
6 James M 12 57.3 83.0 .
7 Jane F 12 59.8 84.5 .
8 Janet F 15 62.5 112.5 .
9 Jeffrey M 13 62.5 84.0 .
10 John M 12 59.0 99.5 .
11 Joyce F 11 51.3 50.5 .
12 Judy F 14 64.3 90.0 .
13 Louise F 12 56.3 77.0 .
14 Mary F 15 66.5 112.0 .
15 Philip M 16 72.0 150.0 .
16 Robert M 12 64.8 128.0 .
17 Ronald M 15 67.0 133.0 .
18 Thomas M 11 57.5 85.0 .
19 William M 15 66.5 112.0 .
Obs name score Sex Age Height Weight
1 Alfred 85 M 14 69.0 112.5
2 Alice 89 F 13 56.5 84.0
3 . F 13 65.3 98.0
4 . F 14 62.8 102.5
5 . M 14 63.5 102.5
6 . M 12 57.3 83.0
7 . F 12 59.8 84.5
8 . F 15 62.5 112.5
9 . M 13 62.5 84.0
10 . M 12 59.0 99.5
11 . F 11 51.3 50.5
12 . F 14 64.3 90.0
13 . F 12 56.3 77.0
14 . F 15 66.5 112.0
15 . M 16 72.0 150.0
16 . M 12 64.8 128.0
17 . M 15 67.0 133.0
18 . M 11 57.5 85.0
19 . M 15 66.5 112.0full join
2 data class2;
3 input name $ score;
4 datalines;
NOTE: The data set WORK.CLASS2 has 3 observations and 2 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
8 ;
9 run;
10
11 proc sql;
12 create table class_e as
13 select *
14 from sashelp.class as a
15 full join class2 as b
16 on a.name = b.name;
WARNING: Variable name already exists on file WORK.CLASS_E.
NOTE: Table WORK.CLASS_E created, with 20 rows and 6 columns.
17 quit;
NOTE: PROCEDURE SQL used (Total process time):
real time 0.00 seconds
cpu time 0.01 seconds
18
19 proc print data=class_e;
20 run;
NOTE: There were 20 observations read from the data set WORK.CLASS_E.
NOTE: The PROCEDURE PRINT printed page 1.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
21 Obs Name Sex Age Height Weight score
1 Alfred M 14 69.0 112.5 85
2 Alice F 13 56.5 84.0 89
3 Barbara F 13 65.3 98.0 .
4 Carol F 14 62.8 102.5 .
5 . . . 99
6 Henry M 14 63.5 102.5 .
7 James M 12 57.3 83.0 .
8 Jane F 12 59.8 84.5 .
9 Janet F 15 62.5 112.5 .
10 Jeffrey M 13 62.5 84.0 .
11 John M 12 59.0 99.5 .
12 Joyce F 11 51.3 50.5 .
13 Judy F 14 64.3 90.0 .
14 Louise F 12 56.3 77.0 .
15 Mary F 15 66.5 112.0 .
16 Philip M 16 72.0 150.0 .
17 Robert M 12 64.8 128.0 .
18 Ronald M 15 67.0 133.0 .
19 Thomas M 11 57.5 85.0 .
20 William M 15 66.5 112.0 . or using merge for appending
data class2;
input name $ score;
datalines;
Alfred 85
Alice 89
Daniel 99
;
run;
data class_f;
merge sashelp.class class2;
by name;
run;
proc print data=class_f;
run;
Obs Name Sex Age Height Weight score
1 Alfred M 14 69.0 112.5 85
2 Alice F 13 56.5 84.0 89
3 Barbara F 13 65.3 98.0 .
4 Carol F 14 62.8 102.5 .
5 Daniel . . . 99
6 Henry M 14 63.5 102.5 .
7 James M 12 57.3 83.0 .
8 Jane F 12 59.8 84.5 .
9 Janet F 15 62.5 112.5 .
10 Jeffrey M 13 62.5 84.0 .
11 John M 12 59.0 99.5 .
12 Joyce F 11 51.3 50.5 .
13 Judy F 14 64.3 90.0 .
14 Louise F 12 56.3 77.0 .
15 Mary F 15 66.5 112.0 .
16 Philip M 16 72.0 150.0 .
17 Robert M 12 64.8 128.0 .
18 Ronald M 15 67.0 133.0 .
19 Thomas M 11 57.5 85.0 .
20 William M 15 66.5 112.0 . inner join
2 data class2;
3 input name $ score;
4 datalines;
NOTE: The data set WORK.CLASS2 has 3 observations and 2 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
8 ;
9 run;
10
11 proc sql;
12 create table class_e as
13 select *
14 from sashelp.class as a
15 inner join class2 as b
16 on a.name = b.name;
WARNING: Variable name already exists on file WORK.CLASS_E.
NOTE: Table WORK.CLASS_E created, with 2 rows and 6 columns.
17 quit;
NOTE: PROCEDURE SQL used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
18
19 proc print data=class_e;
20 run;
NOTE: There were 2 observations read from the data set WORK.CLASS_E.
NOTE: The PROCEDURE PRINT printed page 1.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
21 Obs Name Sex Age Height Weight score
1 Alfred M 14 69.0 112.5 85
2 Alice F 13 56.5 84.0 89 minus join
2 data class2;
3 input name $ score;
4 datalines;
NOTE: The data set WORK.CLASS2 has 3 observations and 2 variables.
NOTE: DATA statement used (Total process time):
real time 0.00 seconds
cpu time 0.00 seconds
8 ;
9 run;
10
11 proc sql;
12 create table class_e as
13 select *
14 from sashelp.class as a
15 left join class2 as b
16 on a.name = b.name
17 where b.name is NULL;
WARNING: Variable name already exists on file WORK.CLASS_E.
NOTE: Table WORK.CLASS_E created, with 17 rows and 6 columns.
18 quit;
NOTE: PROCEDURE SQL used (Total process time):
real time 0.00 seconds
cpu time 0.01 seconds
19
20 proc print data=class_e;
21 run;
NOTE: There were 17 observations read from the data set WORK.CLASS_E.
NOTE: The PROCEDURE PRINT printed page 1.
NOTE: PROCEDURE PRINT used (Total process time):
real time 0.01 seconds
cpu time 0.01 seconds
22 Obs Name Sex Age Height Weight score
1 Barbara F 13 65.3 98.0 .
2 Carol F 14 62.8 102.5 .
3 Henry M 14 63.5 102.5 .
4 James M 12 57.3 83.0 .
5 Jane F 12 59.8 84.5 .
6 Janet F 15 62.5 112.5 .
7 Jeffrey M 13 62.5 84.0 .
8 John M 12 59.0 99.5 .
9 Joyce F 11 51.3 50.5 .
10 Judy F 14 64.3 90.0 .
11 Louise F 12 56.3 77.0 .
12 Mary F 15 66.5 112.0 .
13 Philip M 16 72.0 150.0 .
14 Robert M 12 64.8 128.0 .
15 Ronald M 15 67.0 133.0 .
16 Thomas M 11 57.5 85.0 .
17 William M 15 66.5 112.0 . *** Load utility macros;
%include "C:\Users\hed2\Downloads\mybook2\mybook2\sasmacro\create_table1.sas";
*** Specify input and output data sets, and the column variable.;
%let INPUT_DATA = sashelp.class;
%let OUTPUT_DATA = Table1 ;
%let COLVAR = sex;
/*chort*/
*** %AddText(text=Height);
*** %CategoricalRowVar2(rowVar=);
%ContinuousRowVar2(rowVar=height );
*** %AddText(text=);
%ContinuousRowVar2(rowVar=weight );
%ContinuousRowVar2(rowVar=Age );
proc print data= table1;
run;
/* Export Table 1 as a CSV file*/
proc export data=Table1 replace label
outfile="C:\Users\hed2\Downloads\mybook2\mybook2\sasmacro\table1.csv"
dbms=csv;
run;
Obs Variable freqpct_meansd
1 Height : Mean (SD) [N] 62.3 (5.1) [19]
2 Weight : Mean (SD) [N] 100.0 (22.8) [19]
3 Age : Mean (SD) [N] 13.3 (1.5) [19]
freqpct_meansd_
Obs g1 freqpct_meansd_g2 Prob
1 60.6 (5.0) [9] 63.9 (4.9) [10] 0.1943
2 90.1 (19.4) [9] 109.0 (22.7) [10] 0.1476
3 13.2 (1.4) [9] 13.4 (1.6) [10] 0.8695 *** Load utility macros;
%include "C:\Users\hed2\Downloads\mybook2\mybook2\sasmacro/Utility Macros_updated_NG.sas";
/*
By counts
%let yourdata = sashelp.class;
%let output_data= By_sex;
%let formatsfolder= ;
%let yourfolder = ;
%let varlist_cat = ;
%let varlist_cont = age heigt weight;
%let output_order = height weight age;
%let decimal_max =3;
%let group_by = sex;
%let group_by_missing=0;
%Table_summary;
*/proc glm data= sashelp.class;
model height=age;
Run; The GLM Procedure
Number of Observations Read 19
Number of Observations Used 19
The GLM Procedure
Dependent Variable: Height
Sum of
Source DF Squares Mean Square F Value Pr > F
Model 1 311.5434756 311.5434756 32.77 <.0001
Error 17 161.6207349 9.5071021
Corrected Total 18 473.1642105
R-Square Coeff Var Root MSE Height Mean
0.658426 4.946287 3.083359 62.33684
Source DF Type I SS Mean Square F Value Pr > F
Age 1 311.5434756 311.5434756 32.77 <.0001
Source DF Type III SS Mean Square F Value Pr > F
Age 1 311.5434756 311.5434756 32.77 <.0001
Standard
Parameter Estimate Error t Value Pr > |t|
Intercept 25.22388451 6.52168912 3.87 0.0012
Age 2.78713911 0.48688163 5.72 <.0001